• Journal of KIISE:Databases
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• v.27 no.2
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• pp.247-255
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• 2000

Traditional object decomposition techniques do not decompose spatial objects dynamically during spatial joins, because the object decomposition is very expensive. In this paper, we propose a modified object decomposition technique that can be applied in PBSM(Partition Based Spatial Merge-Join). In real-life data, there are much differences among the sizes of objects. We decompose only large objects with great effects on spatial joins. This technique decreases the decomposition cost of objects during spatial joins and enables efficient filter-refinement steps. Experiments show that the PBSM used with our proposed method performs significantly better than the traditional PBSM.

• Journal of Korea Multimedia Society
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• v.20 no.6
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• pp.845-852
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• 2017

In this paper, we propose a binarization algorithm using LVQ-Merge clustering method for fast and accurate extraction of cells from cell images. The proposed method clusters pixel data of a given image by using LVQ to remove noise and divides the result into two clusters by applying a hierarchical clustering algorithm to improve the accuracy of binarization. As a result, the execution speed is somewhat slower than that of the conventional LVQ or Otsu algorithm. However, the results of the binarization have very good quality and are almost identical to those judged by the human eye. Especially, the bigger and the more complex the image, the better the binarization quality. This suggests that the proposed method is a useful method for medical image processing field where high-resolution and huge medical images must be processed in real time. In addition, this method is possible to have many clusters instead of two cluster, so it can be used as a method to complement a hierarchical clustering algorithm.

• Journal of Korea Multimedia Society
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• v.12 no.12
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• pp.1710-1717
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• 2009

Flash memory has become the most important storage media in mobile devices along with its attractive features such as low power consumption, small size, light weight, and shock resistance. However, a flash memory can not be written before erased because of its erase-before-write characteristic, which lead to some garbage collection when there is not enough space to use. In this paper, we propose a novel garbage collection scheme, called block-level buffer garbage collection. When it is need to do merge operation during garbage collection, the proposed scheme does not merge the data block and corresponding log block but also search the block-level buffer to find the corresponding block which will be written to flash memory in the next future, and then decide whether merge it in advance or not. Our experimental results show that the proposed technique improves the flash performance up to 4.6% by reducing the unnecessary block erase numbers and page copy numbers.

• Database Research
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• v.34 no.3
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• pp.14-27
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• 2018

Recently, to alleviate the memory bottleneck problme occurred in Symmetric Multiprocessing (SMP) architecture, Non-Uniform Memory Access (NUMA) architecture was proposed. In addition, since an aggregation operator is an important operator providing properties and summary of data, the efficiency of the aggregation operator is crucial to overall performance of a system. Thus, in this paper, we propose an efficient aggregation processing technique on NUMA architecture. Our proposed technique consists of partition phase and merge phase. In the partition phase, the target relation is partitioned into several partial relations according to grouping attribute. Thus, since each thread can process aggregation operator on partial relation independently, we prevent the remote memory access during the merge phase. Furthermore, at the merge phase, we improve the performance of the aggregation processing by letting each thread compute aggregation with a local hash table as well as avoiding lock contention to merge aggregation results generated by all threads into one.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.5
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• pp.249-258
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• 2019

In the cyber-physical system, big data collected from numerous sensors and IoT devices is transferred to the Cloud for processing and analysis. When transferring data to the Cloud, merging data into one single file is more efficient than using the data in the form of split files. However, current merging and splitting operations are performed at the user-level and require many I / O requests to memory and storage devices, which is very inefficient and time-consuming. To solve this problem, this paper proposes kernel-level partitioning and combining operations. At the kernel level, splitting and merging files can be done with very little overhead by modifying the file system metadata. We have designed the proposed algorithm in detail and implemented it in the Linux Ext4 file system. In our experiments with the real Cloud storage system, our technique has achieved a transfer time of up to only 17% compared to the case of transferring split files. It also confirmed that the time required can be reduced by up to 0.5% compared to the existing user-level method.

• Journal of Computing Science and Engineering
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• v.3 no.2
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• pp.109-126
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• 2009

Taxonomies are widely used to classify information, and multiple (possibly competing) taxonomies often exist for the same domain. Given a set of correspondences between two taxonomies, it is often necessary to "merge" the taxonomies, thereby creating a unied taxonomy (e.g., that can then be used by data integration and discovery applications). We present an algorithm for merging taxonomies that have been related using articulations given as RCC-5 constraints. Two taxa Nand M can be related using (disjunctions of) the ve base relations in RCC-5: M; N ${\subseteq}$M; N ${\supseteq}$; N ${\oplus}$M (partial overlap of Nand M); and N ! M (disjointness: N ${\cap}$M = ${\varnothing}$). RCC-5 is increasingly being adopted by scientists to specify mappings between large biological taxonomies. We discuss the properties of the proposed merge algorithm and evaluate our approach using real-world taxonomies.

• Journal of Korean Society for Geospatial Information Science
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• v.2 no.1 s.3
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• pp.93-98
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• 1994

This image of Kangseogu in Pusan, is a digital merge of aerial photos by scale of 1/1,200 map. The merge was carried out 2nd affine and bilinear interpolation. It can improve digital classification to help choose training sites and interprete classification results, and improve visual interpretation, as in this case, by adding detailed information to the multispectral TM data.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.5 s.23
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• pp.45-51
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• 2002

The goal of image merging techniques are to enhance the resolution of low-resolution images using the detail information of the high-resolution images. Among the several image merging methods, wavelet-based image merging techniques have the advantages of efficient decorrelation of image bands and time-scale analysis. However, they have no regard for spatial information between the bands. In other words, multiresolution data merging methods merge the same information-the detail information of panchromatic image-with other band images, without considering specific characteristics. Therefore, a merged image contains much unnecessary information. In this paper, we discussed this 'mixing' effect and, proposed a method to classify the detail information of the panchromatic image according to the spatial and spectral characteristics, and to minimize distortion of the merged image.

• Proceedings of the ESK Conference
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• 1995.10a
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• pp.13-17
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• 1995

A Psychophysical scaling method called magnitude estimation is frequently used to evaluate human sensation to physical stimuli. This paper described the procedure of magnitude estimation data analysis which consists of four modulus; reponse space, CMM(Cross-Modality Matdhing)/merge, standardization, scale building & data analysis method. This procedure is being developed as an expert system in which the four analysis modulus are programmed so that a novice user can perform the analysis.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1053-1056
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• 1999

Video On Demand servers generally require massive disk storages for storing many video data. Many researches have been done on the topics of efficient allocation of movies in disks. This paper, We describe efficient disk placement techniques and implement storage system with SCSI and PCI Bus interface for efficient data handling. This paper also proposes a logical zone reconstruction method for the SCAN data placement technique. The proposed method reconstructs physical zones into logical zones by split and merge operations.